linting

ocf_data_sampler/config/model.py

@@ -5,9 +5,9 @@
 """
 
 from collections.abc import Iterator
-from typing_extensions import override
 
 from pydantic import BaseModel, Field, RootModel, field_validator, model_validator
+from typing_extensions import override
 
 from ocf_data_sampler.constants import NWP_PROVIDERS
 

ocf_data_sampler/constants.py

@@ -1,9 +1,8 @@
 """Constants for the package."""
 
-from typing_extensions import override
-
 import numpy as np
 import xarray as xr
+from typing_extensions import override
 
 NWP_PROVIDERS = [
     "ukv",

ocf_data_sampler/select/fill_time_periods.py

@@ -18,6 +18,6 @@ def fill_time_periods(time_periods: pd.DataFrame, freq: pd.Timedelta) -> pd.Date
     end_dts = pd.to_datetime(time_periods["end_dt"].values)
     date_ranges = [
         pd.date_range(start_dt, end_dt, freq=freq)
-        for start_dt, end_dt in zip(start_dts, end_dts)
+        for start_dt, end_dt in zip(start_dts, end_dts, strict=False)
         ]
     return pd.DatetimeIndex(np.concatenate(date_ranges))

ocf_data_sampler/select/find_contiguous_time_periods.py

@@ -5,7 +5,6 @@
 
 from ocf_data_sampler.load.utils import check_time_unique_increasing
 
-
 ZERO_TDELTA = pd.Timedelta(0)
 
 
@@ -80,7 +79,6 @@ def trim_contiguous_time_periods(
     Returns:
       The contiguous_time_periods pd.DataFrame with the `start_dt` and `end_dt` columns updated.
     """
-
     # Make a copy so the data is not edited in place.
     trimmed_time_periods = contiguous_time_periods.copy()
     trimmed_time_periods["start_dt"] -= interval_start
@@ -109,9 +107,8 @@ def find_contiguous_t0_periods(
         pd.DataFrame where each row represents a single time period.  The pd.DataFrame
             has two columns: `start_dt` and `end_dt` (where 'dt' is short for 'datetime').
     """
-
     check_time_unique_increasing(datetimes)
-    
+
     total_duration = interval_end - interval_start
 
     contiguous_time_periods = find_contiguous_time_periods(
@@ -163,7 +160,7 @@ def find_contiguous_t0_periods_nwp(
     # Sanity checks.
     if len(init_times) == 0:
         raise ValueError("No init-times to use")
-    
+
     check_time_unique_increasing(init_times)
 
     if max_staleness < pd.Timedelta(0):

ocf_data_sampler/select/geospatial.py

@@ -10,9 +10,9 @@
 """
 
 import numpy as np
-import xarray as xr
 import pyproj
 import pyresample
+import xarray as xr
 
 # Coordinate Reference System (CRS) identifiers
 # OSGB36: UK Ordnance Survey National Grid (easting/northing in meters)
@@ -118,7 +118,7 @@ def coordinates_to_geostationary_area_coords(
         Geostationary coords: x, y
     """
     if crs_from not in [OSGB36, WGS84]:
-        raise ValueError(f"Unrecognized coordinate system: {crs_from}")    
+        raise ValueError(f"Unrecognized coordinate system: {crs_from}")
 
     area_definition_yaml = xr_data.attrs["area"]
 

ocf_data_sampler/select/location.py

@@ -8,10 +8,10 @@
 class Location(BaseModel):
     """Represent a spatial location."""
 
-    coordinate_system: str = Field(..., 
-        description="Coordinate system for the location must be lon_lat, osgb, or geostationary"
+    coordinate_system: str = Field(...,
+        description="Coordinate system for the location must be lon_lat, osgb, or geostationary",
     )
-    
+
     x: float = Field(..., description="x coordinate - i.e. east-west position")
     y: float = Field(..., description="y coordinate - i.e. north-south position")
     id: int | None = Field(None, description="ID of the location - e.g. GSP ID")

ocf_data_sampler/select/select_time_slice.py

@@ -13,7 +13,7 @@ def select_time_slice(
     time_resolution: pd.Timedelta,
 ) -> xr.DataArray:
     """Select a time slice from a DataArray.
-    
+
     Args:
         da: The DataArray to slice from
         t0: The init-time
@@ -41,7 +41,7 @@ def select_time_slice_nwp(
     accum_channels: list[str] | None = None,
 ) -> xr.DataArray:
     """Select a time slice from an NWP DataArray.
-    
+
     Args:
         da: The DataArray to slice from
         t0: The init-time
@@ -54,16 +54,16 @@ def select_time_slice_nwp(
     """
     if accum_channels is None:
         accum_channels = []
-    
+
     if dropout_timedeltas is not None:
         if not all(t < pd.Timedelta(0) for t in dropout_timedeltas):
             raise ValueError("dropout timedeltas must be negative")
         if len(dropout_timedeltas) < 1:
             raise ValueError("dropout timedeltas must have at least one element")
-    
+
     if not (0 <= dropout_frac <= 1):
         raise ValueError("dropout_frac must be between 0 and 1")
-    
+
     consider_dropout = (dropout_timedeltas is not None) and dropout_frac > 0
 
     # The accumatated and non-accumulated channels

ocf_data_sampler/torch_datasets/datasets/pvnet_uk.py

@@ -1,12 +1,12 @@
 """Torch dataset for UK PVNet."""
 
 from importlib.resources import files
-from typing_extensions import override
 
 import numpy as np
 import pandas as pd
 import xarray as xr
 from torch.utils.data import Dataset
+from typing_extensions import override
 
 from ocf_data_sampler.config import Configuration, load_yaml_configuration
 from ocf_data_sampler.constants import NWP_MEANS, NWP_STDS, RSS_MEAN, RSS_STD

ocf_data_sampler/torch_datasets/datasets/site.py

@@ -1,12 +1,12 @@
 """Torch dataset for sites."""
 
 import logging
-from typing_extensions import override
 
 import numpy as np
 import pandas as pd
 import xarray as xr
 from torch.utils.data import Dataset
+from typing_extensions import override
 
 from ocf_data_sampler.config import Configuration, load_yaml_configuration
 from ocf_data_sampler.constants import NWP_MEANS, NWP_STDS, RSS_MEAN, RSS_STD

tests/test_sample/test_base.py

@@ -3,11 +3,11 @@
 """
 
 from pathlib import Path
-from typing_extensions import override
 
 import numpy as np
 import pytest
 import torch
+from typing_extensions import override
 
 from ocf_data_sampler.sample.base import SampleBase, batch_to_tensor, copy_batch_to_device